Changjiang Wu

980 total citations · 1 hit paper
24 papers, 765 citations indexed

About

Changjiang Wu is a scholar working on Global and Planetary Change, Mechanics of Materials and Ecology. According to data from OpenAlex, Changjiang Wu has authored 24 papers receiving a total of 765 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Global and Planetary Change, 6 papers in Mechanics of Materials and 5 papers in Ecology. Recurrent topics in Changjiang Wu's work include Atmospheric and Environmental Gas Dynamics (6 papers), Land Use and Ecosystem Services (6 papers) and Hydrocarbon exploration and reservoir analysis (6 papers). Changjiang Wu is often cited by papers focused on Atmospheric and Environmental Gas Dynamics (6 papers), Land Use and Ecosystem Services (6 papers) and Hydrocarbon exploration and reservoir analysis (6 papers). Changjiang Wu collaborates with scholars based in China, United States and Netherlands. Changjiang Wu's co-authors include Fengsong Pei, Youyue Wen, Xia Li, Xiaoping Liu, Yi Zhou, Yuchao Yan, Yiling Cai, Klaus Hubacek, Li Xu and Shuanjin Wang and has published in prestigious journals such as Nature Communications, The Science of The Total Environment and Agricultural and Forest Meteorology.

In The Last Decade

Changjiang Wu

23 papers receiving 751 citations

Hit Papers

Global urban expansion offsets climate-driven increases i... 2019 2026 2021 2023 2019 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Global urban expansion offsets climate-driven increases in terrestrial net primary productivity
    2019 293 citations Xiaoping Liu, Fengsong Pei et al. Nature Communications profile →

Peers

Changjiang Wu
Qingwei Zhuang China
Hengmao Wang China
Sean Crowell United States
N. Parazoo United States
Ingrid T. Luijkx Netherlands
Yanning Guan China
Dongxu Yang China
Juan He China
Jiyao Zhao China
Mingliang Liu China
Qingwei Zhuang China
Changjiang Wu
Citations per year, relative to Changjiang Wu Changjiang Wu (= 1×) peers Qingwei Zhuang

Countries citing papers authored by Changjiang Wu

Since Specialization
Citations

This map shows the geographic impact of Changjiang Wu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Changjiang Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Changjiang Wu more than expected).

Fields of papers citing papers by Changjiang Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Changjiang Wu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Changjiang Wu. The network helps show where Changjiang Wu may publish in the future.

Co-authorship network of co-authors of Changjiang Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Changjiang Wu. A scholar is included among the top collaborators of Changjiang Wu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Changjiang Wu. Changjiang Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wu, Changjiang, Xiaoping Liu, Fengsong Pei, et al.. (2025). Non-negligible large impact of potential forestation on livestock production in China. Geography and sustainability. 6(4). 100270–100270. 2 indexed citations
2.
Cai, Yaotong, Peng Zhu, Xing Li, et al.. (2025). Dynamics of China's forest carbon storage: the first 30 m annual aboveground biomass mapping from 1985 to 2023. Earth system science data. 17(12). 6993–7018.
3.
4.
Liu, Xiaoping, Bingjie Li, Changjiang Wu, et al.. (2024). Mapping high-resolution global gridded population distribution from 1870 to 2100. The Science of The Total Environment. 955. 176867–176867. 1 indexed citations
5.
Wang, Shuanjin, Xiangjie Chen, Rui Xie, et al.. (2024). Demand-side insights for steering human appropriation of net primary productivity within planetary boundaries. One Earth. 7(4). 650–662. 22 indexed citations
6.
7.
Cai, Yiling, Xiaoping Liu, Li Zeng, et al.. (2023). Human activities significantly impact China’s net primary production variation from 2001 to 2020. Progress in Physical Geography Earth and Environment. 48(2). 251–274. 5 indexed citations
8.
Lei, Liping, et al.. (2022). Global land 1° mapping dataset of XCO2 from satellite observations of GOSAT and OCO-2 from 2009 to 2020. Big Earth Data. 7(1). 170–190. 32 indexed citations
9.
Liu, Xiaoping, et al.. (2021). Mapping Multi-Temporal Population Distribution in China from 1985 to 2010 Using Landsat Images via Deep Learning. Remote Sensing. 13(17). 3533–3533. 18 indexed citations
10.
Yan, Yuchao, Changjiang Wu, & Youyue Wen. (2021). Determining the impacts of climate change and urban expansion on net primary productivity using the spatio-temporal fusion of remote sensing data. Ecological Indicators. 127. 107737–107737. 52 indexed citations
11.
Liu, Xiaoping, Xun Liang, Yuchao Yan, et al.. (2021). Tensor‐CA: A high‐performance cellular automata model for land use simulation based on vectorization and GPU. Transactions in GIS. 26(2). 755–778. 8 indexed citations
12.
He, Zhonghua, Liping Lei, Yuhui Zhang, et al.. (2020). Spatio-Temporal Mapping of Multi-Satellite Observed Column Atmospheric CO2 Using Precision-Weighted Kriging Method. Remote Sensing. 12(3). 576–576. 55 indexed citations
13.
Liu, Xiaoping, Fengsong Pei, Youyue Wen, et al.. (2019). Global urban expansion offsets climate-driven increases in terrestrial net primary productivity. Nature Communications. 10(1). 5558–5558. 293 indexed citations breakdown →
14.
Zhou, Yi, Fengsong Pei, Yan Xia, et al.. (2019). Assessing the Impacts of Extreme Climate Events on Vegetation Activity in the North South Transect of Eastern China (NSTEC). Water. 11(11). 2291–2291. 7 indexed citations
15.
Lei, Liping, Zhao‐Cheng Zeng, Bofeng Cai, et al.. (2018). Regional uncertainty of GOSAT XCO 2 retrievals in China: quantification and attribution. Atmospheric measurement techniques. 11(3). 1251–1272. 22 indexed citations
16.
Pei, Fengsong, Changjiang Wu, Xiaoping Liu, et al.. (2018). Detection and attribution of extreme precipitation changes from 1961 to 2012 in the Yangtze River Delta in China. CATENA. 169. 183–194. 44 indexed citations
17.
Lei, Liping, Hui Zhong, Zhonghua He, et al.. (2017). Assessment of atmospheric CO<sub>2</sub> concentration enhancement from anthropogenic emissions based on satellite observations. Chinese Science Bulletin (Chinese Version). 62(25). 2941–2950. 15 indexed citations
18.
Pei, Fengsong, Changjiang Wu, Xiaoping Liu, et al.. (2017). Monitoring the vegetation activity in China using vegetation health indices. Agricultural and Forest Meteorology. 248. 215–227. 136 indexed citations
19.
Pei, Fengsong, et al.. (2017). Changes in Extreme Precipitation: A Case Study in the Middle and Lower Reaches of the Yangtze River in China. Water. 9(12). 943–943. 18 indexed citations
20.
Zhao, Jianlin, et al.. (2005). Necessity analyses of phase masks in joint fractional Fourier transform correlator. Optics Communications. 259(2). 526–531. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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